Pericarp thickness of sorghum whole grain is accurately predicted by NIRS and can affect the prediction of other grain quality parameters

Guindo Diarah, Davrieux Fabrice, Teme Niaba, Vaksmann Michel, Doumbia Mohamed, Fliedel Geneviève, Bastianelli Denis, Verdeil Jean-Luc, Mestres Christian, Kouressy Mamoutou, Courtois Brigitte, Rami Jean-François. 2016. Pericarp thickness of sorghum whole grain is accurately predicted by NIRS and can affect the prediction of other grain quality parameters. Journal of Cereal Science, 69 : pp. 218-227.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Quartile : Q2, Sujet : FOOD SCIENCE & TECHNOLOGY

Abstract : The thickness of grain pericarp, the outer layer of the kernel, is an important breeding criterion for sorghum. This cereal is mainly used through traditional processing in family-based food systems in many regions of the world. We investigated in this study how pericarp thickness could be predicted by Near Infrared Reflectance Spectroscopy (NIRS), a fast and non-destructive measurement method that is commonly used to measure physico-chemical parameters of sorghum grains, and how this trait also influences the prediction of those parameters. We showed that, using a classification approach, it was possible to discriminate thick from thin pericarp whole grain samples with a good accuracy and that the proportion of thin and thick grains in mixed samples could also be predicted. In addition, pericarp thickness had a significant effect on the calibration performance for other grain parameters indicating that the pericarp can distort spectral information of whole grain samples. As a practical consequence, we suggest to develop separate whole grain calibration models for thin and thick pericarp samples, combined with a two-steps prediction approach to improve the accuracy of whole grain NIRS calibrations for grain quality parameters in sorghum. (Résumé d'auteur)

Mots-clés Agrovoc : Sorghum, Péricarpe, Épaisseur, Grain, Spectroscopie infrarouge, Sélection, Amélioration des plantes, technique de prévision, Qualité

Mots-clés géographiques Agrovoc : Monde

Classification Agris : F60 - Plant physiology and biochemistry
U30 - Research methods
F30 - Plant genetics and breeding

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Guindo Diarah, CIRAD-BIOS-UMR AGAP (FRA)
  • Davrieux Fabrice, CIRAD-PERSYST-UMR Qualisud (REU)
  • Teme Niaba, IER (MLI)
  • Vaksmann Michel, CIRAD-BIOS-UMR AGAP (MLI) ORCID: 0000-0002-5258-1279
  • Doumbia Mohamed, IER (MLI)
  • Fliedel Geneviève, CIRAD-PERSYST-UMR Qualisud (FRA)
  • Bastianelli Denis, CIRAD-ES-UMR SELMET (FRA) ORCID: 0000-0002-6394-5920
  • Verdeil Jean-Luc, CIRAD-BIOS-UMR AGAP (FRA)
  • Mestres Christian, CIRAD-PERSYST-UMR Qualisud (FRA)
  • Kouressy Mamoutou, IER (MLI)
  • Courtois Brigitte, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0003-2118-7102
  • Rami Jean-François, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0002-5679-3877

Source : Cirad-Agritrop (

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